Methods and systems for wave slam monitoring of water vessels

ABSTRACT

A method of monitoring wave slam on a vessel includes measuring acceleration forces from mechanical shocks on the vessel using one or more sensors communicatively coupled to a computing unit. Generating real-time acceleration information representative of the wave slam based at least in part on the data obtained from the sensors. Generating acceleration prediction information representative of a predicted wave slam based at least in part on the generated real-time acceleration information. Presenting at least one of the generated real-time acceleration information or acceleration prediction information to an intended recipient.

BACKGROUND Background and Relevant Art

Small craft vessels that average from 3 to 20 meters in length and arecapable of reaching speeds in excess of 20 knots are often referred toas planing crafts or planing vessels. They can serve multiple purposesand are used by various organizations. The types of crafts and theorganizations that use them include: special-purpose crafts, used bynavies, coast guards, search and rescue associations, customs patrol,and law enforcement; specialized work crafts, used in fishing and fishfarming, and by offshore oil and windfarms, and research projects;tourist cruise crafts, used by expedition companies, whale-watchingcompanies, boat charters, sea safari companies, snorkeling companies;yacht tenders and chase boats, used for transportation by yacht ownersand charter companies; or simply as personal watercrafts used by privateowners.

While planing craft vessel types and their use are both various andwidespread, the hull forms on which they are built tend to be verysimilar. These hulls are typically referred to as planing hulls due tothe way they rise up and glide, or plane, on top of the water whenenough power is supplied by propulsion mechanisms. This allows planinghulls to travel rapidly across the water. Alternatively, larger vesselstend to be built on displacement hulls due to the increased propulsionpower needed to get them up to plane. These vessels having displacementhulls are limited to slower speeds as they move through the water bypushing the water aside.

Vessels with planing hulls tend to operate in a similar fashion todisplacement hulls when at slow speeds, but as they move faster, theyclimb vertically to the surface of the water. Vessels with planing hullstend to ride almost on top of the water, minimizing friction and waterdisplacement, allowing them to reach high speeds.

Planing hulls however have a large drawback. Particularly, a planingvessel will dip its stern downwards while the bow rises vertically outof the water as the vessel picks up speed. As the front of the hull isout of the water, waves that hit the vessel from the front will forcethe vessel to surge longitudinally out of the water, causing it to jumpand aggressively slam down again. Likewise, waves that hit from the sidewill cause the vessel to sway in a port-starboard motion.

These movements can cause intense mechanical shocks that can lead toboth acute and chronic physiological problems for operators andpassengers, and mechanical problems for vessels and expensive equipmentonboard, due to the excessive accelerations that result from suchimpacts. A study was conducted by the Naval Health Research Center onself-reported injuries among special boat operators in the US Navy(Ensign W et al. [2000] ‘A Survey Of Self-Reported Injuries AmongSpecial Boat Operators’ Naval Health Research Center). The sample meanage of respondents was 32.0±5.9 years, mean years of military servicewas 12.0±5.5 years and the mean time in Special Boats was 4.7±3.0 years,where respondents were asked to report on injuries sustained duringtheir time as Special Boat Operators.

The study found that 65% of operators have suffered injuries caused bythe shocks of wave slamming. The most prevalent type of injury wassprains and strains (49.3%), disc problems (7.9%), and trauma (7.9%).The most prevalent injury sites were the lower back (33.6%), knee(21.5%), and shoulder (14.1%). Injuries like these are costly, as thisstudy showed. These injuries resulted in a total of 145 days ofhospitalization, 440% higher than the overall Navy Average, 929 days ofsick leave, 4,223 days of limited duty, 4,218 days of limited job ormission performance, 2,294 days of lost mission training time, and 4,089days of lost physical conditioning time.

This study clearly showed a relationship between repeated mechanicalshock exposure from wave slamming and injury occurrence. Likewise,another study on the mechanical shock on high speed planing boats, fromthe Department of Ocean Engineering and Mechanical Engineering atMassachusetts Institute of Technology (Kearns, S D. [2001] ‘Analysis andMitigation of Mechanical Shock effects on High Speed Planing Boats.’Department of Mechanical Engineering, Massachusetts Institute ofTechnology), found that a clear correlation clearly exists betweenservice time aboard high-speed boats and an increased rate of acute andchronic injury, where the mechanical shock environment on such vesselsmay be extremely severe depending on sea-state and other environmentaland mechanical factors. The study concluded that shock mitigationsystems currently available are insufficient to protect crew andpassengers from injury and that this is a problem that needs to bebetter addressed.

While no single standard or directive addresses this issue of mechanicalshocks and vibrations in small vessels, the European Directive2002/44/EC addresses the problem of Whole Body Vibrations (WBVs),defined in ISO 2631-1:1997 by creating limitations on human exposure tomechanical vibrations and shocks. While this directive was originallyintended for operators of machinery, and therefore has its limitationsin the marine sector, it has become widely used as a standard fordefining human tolerance of shocks and vibrations in small vessels, andin particular, high speed vessels.

In procurement tenders for high-speed crafts in Europe, public andprivate organizations request that bidders' offerings adhere as closelyas possible to the European Directive 2002/44/EC, which in some cases isused as a criteria for bidder selection. The United States has yet todetermine a defined standard by which bidders' offerings must adhere toin terms of shocks and vibrations.

In the European Directive 2002/44/EC on WBVs, the accepted guidancecaution zone is defined as being above 0.57 g, where impacts above thisvalue are considered to be hazardous. However, many manufacturers andbuyers in the industry disagree with the relevance of this standard, asstaying within the defined caution zone is considered to be unrealisticwhen operating high speed crafts. This is because the standard wasoriginally created to determine the caution zones for prolonged exposureto vibrations, as opposed to the impacts and shocks more relevant tohigh speed crafts.

Several other standards are in place, such as ISO 2631:5 (the relevanceof which is also contested by many), Annex 10 of 2000 HSC CODE:International Code of Safety for High-Speed Craft, and the MCA MarineGuidance Note MGN 436. Guidelines have been put in place, such as theHigh Speed Craft Human Factors Engineering Design Guide, sponsored bythe UK MOD Defence Equipment & Support Agency (DE&S), and the HumanElement Competencies Templates, which help guide procurement agencies,vessel designers and naval architects by placing Human Factors (HF)requirements, which prioritize safety and ergonomic factors, at thecenter of purchasing and design decisions.

Despite this, most planing vessels in operation today are stilldetrimentally impacted by mechanical shocks and vibrations despite thesedirectives, standards and guidelines. Some attempts have been made toimprove the safety of operators and crew on high speed vessels. Forinstance, the most common method of mitigating the harmful effects ofwave slamming is through the use of shock absorbing seats. While the useof shock absorbing seats significantly reduces the impact experienced bythe operator and crew onboard, the impact experienced is stillsignificant and can still cause serious injuries. The use of shockabsorbing seats also does not have any influence on the mechanicalshocks that impact the vessel itself and the equipment onboard, whichsuffer significant wear and tear and degrade faster due to the effect ofthese impacts.

Reducing these mechanical shocks is therefore in the best interest of:vessel operators and crew; vessel owners (including organizations,institutions and/or individuals), and insurance companies (which insureagainst the risk of injury and damage and face the risks associated withhazards). As the issues of mechanical shock exposure become more widelyrecognized and accepted, interest has grown among researchers andorganizations to equip vessels with force-recording sensors for thepurposes of study and analysis.

There is thus a need for a method and/or system for mitigating damage toproperty and injury to personnel caused by mechanical shocks experiencedon vessels and small crafts.

The subject matter claimed herein is not limited to embodiments thatsolve any disadvantages or that operate only in environments such asthose described above. Rather, this background is only provided toillustrate one exemplary technology area where some embodimentsdescribed herein may be practiced.

BRIEF SUMMARY

Embodiments of the present disclosure can include a method andmonitoring system arranged to collect, store and analyze data onacceleration forces from mechanical shocks, optionally along withweather and wind, engine, and/or navigational data, to compute real-timeinformation on acceleration caused by wave slamming, and to makepredictions of the potential of hazardous situations likely to occur inthe near-future on sea journeys.

According to a variation, the embodiments of the present disclosure maypresent real-time information and prediction information to the boatoperator, alerting the operator of current and potential accelerationhazards through visual, sound and vibration alerts. This can includeusing a variety of current and historical information, includingreal-time acceleration forces experienced from mechanical impacts andshocks, current and past sea-states, weather data, engine data,navigation data, etc. to present real-time information on currentacceleration and to make near-future predictions of potential hazardsahead caused by acceleration forces.

For predictions to be reliable and current, embodiments of the presentdisclosure can use values gathered from different batches of historicaland real-time data. These values can be used to make accuratepredictions as to the likely shocks and consequent hazards to occur inthe near-future, for example, for the subsequent one to ten minutes of ajourney. A plurality of sensors and/or instruments can be used to gatherdata, which will be analyzed and stored in a computer implementedcomputing unit onboard the vessel and/or in external databases. Thecomputing unit may be able to utilize various algorithms and artificialintelligence functions for the facilitation of real-time analysis andpredictions. The output of the information analyzed may then bepresented visually, aurally and through vibration, where alarms may betriggered when a pre-determined hazard level is surpassed. This mayallow the operator to make better decisions with the aim of minimizinginjuries and damage caused by mechanical impacts and shocks.Alternatively, or additionally, the output of the information analyzedmay be used to perform automated control of a vessel to avoid impactsand/or mitigate the effect of impacts.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

Additional features and advantages will be set forth in the descriptionwhich follows, and in part will be obvious from the description, or maybe learned by the practice of the teachings herein. Features andadvantages of the invention may be realized and obtained by means of theinstruments and combinations particularly pointed out in the appendedclaims. Features of the present invention will become more fullyapparent from the following description and appended claims, or may belearned by the practice of the invention as set forth hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features can be obtained, a more particular descriptionof the subject matter briefly described above will be rendered byreference to specific embodiments which are illustrated in the appendeddrawings. Understanding that these drawings depict only typicalembodiments and are not therefore to be considered to be limiting inscope, embodiments will be described and explained with additionalspecificity and detail through the use of the accompanying drawings inwhich:

FIG. 1 is a side, starboard, view of a planing hull in three positions,POS 1, POS 2 and POS 3, indicating the direction of accelerationexperienced by the hull in the longitudinal, stern-bow, directionaccording to an embodiment.

FIG. 2 is a back, stern, view of a planing hull in two positions, POS 4and POS 5, indicating the direction of acceleration, or roll,experienced by the hull in the port-starboard, or sway, directionaccording to an embodiment.

FIG. 3 is an isometric view of a planing hull craft, indicating theprimary modules required for the solution. Elements include a planinghull craft, a computing unit, sensors, a display unit, and a mechanicalvibration device according to an embodiment.

FIG. 4 is an isometric view of a planing hull craft, indicating variouselements that interact with and provide additional data input into thesolution according to an embodiment.

FIG. 5 is a chart showing the interactions of the elements according toan embodiment.

FIG. 6 is an isometric view of a multi-axis accelerometer, illustratingthe directions and rotation of acceleration forces that the multi-axisgyroscopic accelerometers measure according to an embodiment.

FIG. 7 is an overview of the acts in an embodiment of the wave slammonitoring method.

FIG. 8 is an overview of a system for wave slam monitoring.

DETAILED DESCRIPTION

A better understanding of different embodiments of the disclosure may behad from the following description read with the accompanying drawings.

While the disclosure is susceptible to various modifications andalternative constructions, certain illustrative embodiments are in thedrawings and are described below. It should be understood, however,there is no intention to limit the disclosure to the specificembodiments disclosed, but on the contrary, the intention covers allmodifications, alternative constructions, combinations, and equivalentsfalling within the spirit and scope of the disclosure.

It will be understood that unless a term is expressly defined in thisapplication to possess a described meaning, there is no intent to limitthe meaning of such term, either expressly or indirectly, beyond itsplain or ordinary meaning.

Any element in a claim that does not explicitly state “means for”performing a specified function, or “step for” performing a specificfunction is not to be interpreted as a “means” or “step” clause asspecified in 35 U.S.C. § 112(f).

Embodiments of the present disclosure advantageously can collect, storeand analyze data on acceleration forces from mechanical shocks to avessel, along with, optionally, weather, wind, engine, and/ornavigational data, to compute real-time information on accelerationexperienced caused by wave slamming, and to make predictions of thepotential of hazardous situations likely to occur in the near-future ona particular sea journey. Furthermore, embodiments of the presentdisclosure may then present the real-time information and predictioninformation to the boat operator, alerting the operator of current andpotential acceleration hazards through visual, aural and/or tactilealerts. Alternatively, or additionally, embodiments may implement and/orassist with automated control of a vessel to avoid wave slamming impactsand/or mitigate damage from such impacts.

To facilitate understanding of the present disclosure, FIGS. 1 and 2illustrate a vessel, which in the present example is a planing hullcraft 1, in various positions along with identifications of associatedmovements and accelerations. Referring initially to FIG. 1, the planinghull craft 1 is illustrated in three positions, POS 1, POS 2 and POS 3,indicating the acceleration forces experienced by the planing hull craft1 in a longitudinal, stern-bow, motion.

Additionally, FIG. 1 shows the movements created both as the planinghull craft 1 climbs onto an incoming wave longitudinally and as it slamsback down when it clears the wave. The acceleration forces created bythe mechanical shocks experienced from the rapid movements through POS1, POS 2 and POS 3 illustrated in FIG. 1 are damaging to operators andcrew, the mechanical structure of the vessel, and equipment onboard. Foroperators and crew, these forces are the leading cause of lower back,and in particular disc, related injuries.

FIG. 2 shows a back, stern, view of a planing hull craft 1 in twopositions, POS 4 and POS 5, indicating the roll, port-starboard, motionsand the acceleration forces they generate experienced by the planinghull craft when waves strike the vessel in the port or starboard sidesof the hull. The roll motion and the mechanical shocks caused, asindicated by POS 4 and POS 5 are some of the leading causes ofknee-related injuries for operators and crew.

Referring to FIGS. 3 and 4, a monitoring/alerting system for detectingand predicting wave slam and alerting a vessel operator of the same caninclude a planing hull craft 1, a computing unit 2, one or more sensors3-6, and a display unit 7. The one or more sensors 3-6 are arranged tocollect acceleration data, which may be computed by the computing unit 2and/or sensors 3-6 as acceleration over time. The measurements may, forexample, be the root mean square values of the number of impactsexperienced over a chosen period of time.

The sensors 3-6 can be positioned in any suitable location on theplaning hull craft 1 for collecting acceleration information. Forinstance, FIGS. 3-6 show four sensors with sensor 3 located in thestern, sensor 4 located on the starboard side, sensor 5 located on thebow, and sensor 6 located on the port side of the planing hull craft 1.The sensors 3 and 5 can be arranged to measure the acceleration causedby longitudinal, bow-stern movements from mechanical shocks impactingthe bow and/or the stern of the planing hull craft 1. The sensors 4 and6 can be arranged to detect and/or measure acceleration caused by sway,port-starboard or starboard-port movements from mechanical shocksimpacting the port or starboard sides of the planing hull craft 1. Itshould be appreciated that other sensor combinations and sensingfunctions may be implemented in other embodiments.

The sensors 3-6 can comprise any suitable sensing unit but areillustrated in the present example as multi-axis gyroscopicaccelerometers 3-6. In an embodiment, measurements from the sensors 3-6may be delivered to the computing unit 2 in various fashions. Forexample, often, such sensors generate a voltage based on movement. Inmany cases, the voltage is an alternating current voltage of aparticular frequency, where the voltage can be correlated to a magnitudeof movement and the frequency can be correlated to a type of movement(such as a vibration, including aftershocks, harmonic resonance, and thelike). Thus, some embodiments may cause measurements from the sensors3-6 to be delivered as root mean square voltage values of the voltagemeasurement and, alternatively or additionally a frequency measurementin Hertz (Hz) or other units of measurement, as is required andapplicable. Other values may be provided depending on the type andconfiguration of sensors. Four sensors 3-6 are shown but embodiments mayinclude any suitable numbers of sensors.

The computing unit 2 is communicatively coupled to sensors 3-6 and canprovide information to an operator and/or remote data representative ofaccelerations from mechanical shocks impacting a vessel or planing hullcraft 1. The computing unit 2 can include an I/O module arranged tocommunicate information between the computing unit 2 and the sensors3-6. The computing unit 2 may be implemented using various items ofcomputing hardware, including processors, memory, storage, communicationhardware, and the like. It will be appreciated that the computing unit 2may also be arranged to communicate information between the computingunit 2 and additional instruments and modules arranged to help themonitoring system to provide more accurate real-time accelerationinformation and acceleration predictions as discussed below. Forinstance, an I/O module of the computing unit 2 can be communicativelycoupled via a network interface card to a communications network module11 (such as a network router or other hardware device) that integratesmarine electronic equipment on vessels (for example, hardware using NMEA2000 protocols), engine data instruments 10, external weather datareceivers 12, wind data instruments 13, GPS receiver(s) 14, and/or anautical chart plotter 15 with the monitoring system.

Optionally, a network connection module 16 can connect differentinstruments so that they can receive and send data via a network. Thenetwork connection module 16 can allow instruments to receive networkconnectivity, such as through 4G, 3G or satellite network connectionhardware 17, and likewise send information to be stored in one or moreexternal databases, when and if applicable. Additionally, the networkconnection module 16 may not be limited to 4G, 3G or a satellite networkconnection, but may also be capable of utilizing other applicable typesof communication networks available, including some that may not yet becommercially or otherwise available. It will be appreciated that themonitoring system of the present disclosure is not limited to theinstruments and modules shown but other instruments and modules arepossible.

Referring to FIG. 5, the system can optionally include primary andadditional or auxiliary modules. For instance, modules 2-9 can compriseprimary modules and modules 10-16 can comprise additional or auxiliarymodules. It will be appreciated that the system can use all or some ofthe modules 2-16. As discussed above, the network connection module 16can be integrated with marine electronic equipment (such as thecommunications network module 10) on vessels (for example, NMEA 2000compliant hardware) so as to operate as an integrated communicationsnetwork for the modules 11-15, receiving data from each and directingthat data from a single source to the computing unit 2 where dataanalysis and generation can be performed. The computing unit 2 mayreceive data inputs from multiple module and/or instrument (e.g., 11-15)sources simultaneously. It will be appreciated that various functions ofthe monitoring system may be executed in whole or in part by thecomputing unit 2, the sensors 3-6, the display unit, and/or other units.

In other embodiments, the primary or auxiliary modules can includeadditional modules. For instance, the modules can include a smart and/oraugmented reality device or eyewear 30 arranged to provide an operatorwith a line-of-sight display of information. Optionally, the augmentedreality eyewear 30 can be arranged for intelligent display ofinformation using a point-of-view camera. In an embodiment, the modulescan include laser imaging and radar instruments 29 arranged to generateand/or present both visual and sensor-based data. For instance, themodules can include 360 degree cameras and Light Detection and Ranging(LIDAR) instruments arranged to provide visual and sensor-based dataincluding, but not limited to, height, length, and distance to one ormore waves. Such information can then be input in a data collectionprocess as discussed below to enhance predicative capabilities of thepresent disclosure.

In other embodiments, the modules present other information. Forexample, the modules can include an auxiliary computing unit 31comprising a fleet management system arranged to present informationrepresentative of a plurality of vessels in real time. In an embodiment,the auxiliary computing unit 31 can comprise a simulation system forboating and/or watercraft simulations. For instance, a simulator may usegenerated data or information to characterize sea states and conditionsfor training or other purposes. A fleet owner may use the auxiliarycomputing unit 31 to monitor a fleet as well as communicate withoperators of craft.

In other embodiments, modules can be operatively coupled to thecomputing unit 2 to help protect an operator from injury. For instance,the modules can include at least one suspension seat 32 operativelycoupled to the computing unit 2 and one or more hydraulic systems suchthat generated/collected data can be used to predict wave slamming andadjust suspension of the suspension seat 32 via control of the one ormore hydraulic systems.

In yet other embodiments, modules can be operatively coupled to thecomputing unit 2 to control navigation of the craft based on informationfrom the one or more sensors. For instance, the modules can include asteering and/or throttle mechanism so that the computing unit 2 canautomatically control direction and/or speed of the craft based oninformation from the one or more sensors. This control can be fullyautomatic, or user assisted as appropriate. The modules can include acruise control system operatively coupled to the computing unit 2 tocontrol throttle and/or trim to reduce the likelihood of wave slammingbased on information from the one or more sensors. Optionally, themodules can include a route guidance system arranged to instruct ordirect an operator to take a specific path through waves to reduce thelikelihood of wave slamming. If the computing unit 2 makes a specificdetermination based on information from the one or more sensors, thecomputing unit 2 may intervene with user control of the throttle and/orsteering systems to override user control, or at least enhance usercontrol by amplifying and/or dampening user control actions asappropriate to reduce wave slamming and/or the effects thereof.

In addition to the foregoing, one will appreciate that embodiments ofthe present disclosure can also be described in terms of flowchartsincluding one or more acts for accomplishing a particular result. Forexample, the acts of FIG. 7 and the corresponding text describe acts forgenerating and providing real-time and prediction information associatedwith wave slam on a water craft. The acts of FIG. 7 are described belowwith respect to the components and modules of FIGS. 1-6.

For instance, FIG. 7 illustrates a method in accordance with the presentdisclosure for generating and providing real-time and predictioninformation associated with wave slam on a water craft. The methodincludes act 18 of collecting data. For example, data may be collectedby generating real-time acceleration information representative of waveslam based at least in part of data obtained from one or more of thesensors 3-6. It will be appreciated that the method can include acts ofmeasuring acceleration forces from mechanical shocks on a vessel usingthe one or more sensors 3-6 and receiving data from the sensors 3-6 bythe computing unit 2. Act 18 can alternatively or additionally includecollecting data from multi-axis gyros, accelerometers, engineinstruments, wind data instruments, external weather data receivers,nautical chart plotters, GPS receivers, depth measuring instruments,integrated communications network modules, wave buoys, lasers, LiDAR,cameras (including 360 degree cameras), or other instruments. In someembodiments, act 18 may include collecting similar types of data fromother vessels communicatively coupled to the craft 1.

Act 18 may further include collecting data about individual vessels. Forexample, devices on the craft 1 may have information that can identifythe craft 1 specifically. For example, the network connection module 16may include identifiers that can be attached to data, where theidentifiers identify the module 16 and/or the craft specifically. Inthis way, accelerations and other measurements can be directlycorrelated to the craft 1. This can be useful when aggregating data frommultiple different vessels as will be illustrated in more detail below.

Act 18 may further include collecting data about individual crew and/orpassengers. For example, embodiments may include data sources thatinclude crew and passenger manifests. In an embodiment, an operator maybe prompted to input personal information into the monitoring systemduring a first monitoring period. For a subsequent monitoring period,the monitoring system may ask the operator for verification of personalinformation so that it can retrieve stored data from previous monitoringperiods or events. This data may be retrieved from a local database ofthe computing unit 2 and/or external databases. This advantageouslyallows the monitoring system to accommodate multiple operators and adaptdata analysis and predictions based on an individual operator'shistorical data. Alternatively, or additionally, vessel controlinformation may be collected for crew members. For example, informationmay be collected from propulsion and steering mechanisms of the craft 1indicating actions performed by an operator to control the craft. Thespecific controls performed can be correlated with a specific operator,other crew member, or even passengers. This data can be collected andused in subsequent acts. For example, embodiments may adjust actionsperformed based on known information about particular crew members orpassengers. For example, embodiments may know that certain operators actin a particular fashion when certain conditions are encountered. Thisinformation can be used to adjust actions performed, such as appropriatealerts and/or automated control actions, as will be illustrated in moredetail below. Indeed, some embodiments may create and maintain anoperator risk profile defining the risk of wave slam and severity ofpotential wave slams correlated to specific operators.

Act 19 can include performing real-time analysis and informationgeneration. This can include analyzing and/or transforming the receivednumerical data from various sensors. For example, data from the sensors3-6 can be analyzed and/or transformed to provide real-time accelerationinformation associated with the wave slam. For instance, the computingunit 2 can receive a single root mean square value from each multi-axisgyroscopic accelerometer 3-6 per second, totaling 4 root mean squarevalues per second. The multi-axis gyroscopic accelerometers 3-6 may becapable of gathering anywhere from two to 2000 measurements per second,which may be averaged into one root mean square output value per secondper multi-axis accelerometer 3-6. Act 18 can include using one or morealgorithms to more accurately determine real-time accelerationinformation with each second based on the multiple root mean squareinputs from the sensors 3-6 (e.g., multi-axis gyroscopic accelerometers3-6), repeating the process continuously while the monitoring system isactive and in use. Note that data from other sensors and sources mayadditionally or alternatively be collected and applied toalgorithmically determine real time acceleration forces, or for use inpredicting acceleration forces as outlined in act 20.

FIG. 7 also show that the method can include the act 20 of performingprediction data analysis and information generation. For example, act 20may include generating acceleration predictions associated with apredicted wave slam based at least in on part on the real-timeacceleration information obtained from act 19 and/or data collected fromvarious sensors and other sources. Act 20 may be performed as togetherwith act 19 or may comprise an independent act. For instance, act 20 mayinclude using analyzed root mean square data from several differentprior time periods, for example, the last ten seconds, the last 5minutes and the last 20 minutes, to analyze and predict potentialnear-future acceleration values. The length of prior time periods usedfor prediction analysis, the time intervals in which data is updated andthe duration of the acceleration predictions may vary based on relevancewhen in the invention solution is in use. Act 20 can be performed atleast in part by the computing unit 2.

FIG. 7 illustrates that the method can include an act 21 of determiningactions to be performed based on prediction data analysis andinformation. In particular, various alerts, notifications, datacollection operations, automated control procedures, and the like can beperformed based on the prediction data analysis and information.

For example, FIG. 7 illustrates that act 21 can cause act 22 to beperformed, which is an act of performing server infrastructure anddatabase processes. In some embodiments, this may further includesending information to a fleet management system as illustrated in act34. Note that in certain embodiments, the data will be sent to theserver infrastructure and database, from where it can be pushed out to afleet management system. In particular, some embodiments may beimplemented where a device on the vessel itself never sends anything tothe fleet management system. Rather, in those embodiments, thedatabase/infrastructure is the “control center.” Note that while acts 22and 34 are illustrated subsequent to act 21, it should be appreciatedthat information can be sent to the server infrastructure and dataset atvirtually any stage of the method. Additionally, data can be receivedfrom the fleet management system and from the server and infrastructuredatabases, such that acts 18, 19, and 20 can be iteratively performedafter, and as a result of acts 22 and 34 as illustrated in FIG. 7.

A number of different advantages can be achieved by storing thehistorical data, analysis, and information. For example, as will beillustrated in more detail below, such information can be used toimplement feedback controls, including basic system feedback controlsand/or artificial intelligence (AI) based feedback controls.

Alternatively or additionally, acts 22 and/or 34 allow records to becompiled documenting impacts experienced by various vessels. Theserecords can be later accessed to facilitate appropriate maintenance ofvessels. Alternatively or additionally, these records can be used toperform valuations of crafts by identifying specific vessels that mayhave potentially been damaged. In some embodiments, these records can beaggregated to identify wave slam and severity of wave slam experiencedby particular types of vessels. Thus, for example, a particularmanufacturer and/or model number may be rated, using collectedinformation, for wave slam propensity.

Alternatively or additionally, acts 22 and/or 34 allow records to becompiled documenting impacts experienced by specific crew members. Theserecords can be later accessed to facilitate appropriate training ofspecific crew members. Alternatively or additionally, these records canbe used to perform hiring and termination decisions for specific crewmembers

Alternatively or additionally the information collected in acts 22and/or 34 may be fed back to act 20 to be used in performing predictivedata analysis. For example, consider the case where acts 22 and 34collect information from a number of different vessels. This informationcan be used when performing act 20 to make predictions for a specificvessel. For example, knowing conditions experienced by vessels proximatethe specific vessel can be used to predict future accelerationsexperienced by the specific vessel. For example, waves experienced by anearby vessel may shortly be experienced by the specific vessel. A wakecaused by a nearby vessel may cause a wave slam impact experienced bythe specific vessel. Knowing about nearby vessels, can thus be used forprediction analysis for a specific vessel.

As noted above, the method may include one or more acts of presentingreal-time acceleration information and/or prediction information to anintended recipient such as an operator. For example, the monitoringsystem may include a screen display (shown in FIGS. 3-5) arranged topresent a graphical visual output of information (e.g. real-timeacceleration information, stored acceleration information, predictioninformation, etc.) to the operator. The information may be in anysuitable form, including, but not limited to forms optimized for,applicability, logic and function, ease of use, understanding, and/orvisual appeal.

In some embodiments the presentation of information may includepresenting an alarm or alert to the operator. For instance, the alarmmay be presented if the information generated in acts 19 and/or 20indicates that real-time acceleration or wave slam has surpassed apre-determined acceleration hazard level. The pre-determinedacceleration hazard level may depend on relevant conditions and usage.In an embodiment, the pre-determined acceleration hazard level may bebased on European Directive 2002/44/EC's caution zone of 0.57 gacceleration, or other standards or criteria. It will be appreciatedthat the alarm may include a visual alarm shown by the display unit 7(see act 23), a tactile (e.g., vibration) alarm output by the vibrationalarm 8 (see act 24) and/or an audible alarm (see act 25) output by theaudible alarm 9. In some embodiments, the presentation of informationmay include presenting via the augmented reality eyewear 30. Forinstance, the computing unit 2 can be operatively coupled with theaugmented reality eyewear 30 to provide the operator with aline-of-sight display.

Note that some embodiments may include functionality for implementingautomated controls. For example, act 28 illustrates an act ofimplementing automated operational control. This may include, forexample, implementing cruise control functions, throttle control, routeguidance, trim control, etc.

Note that this functionality is particularly useful when implementingunmanned vessels. Such functionality may be used to prevent and/orreduce the effects of wave slam. In particular, the automated operationcontrols to prevent and/or reduce the effects of wave slam may beimplemented in conjunction with other automated operation controls fornavigation or other unmanned vessel controls. Indeed, while exampleshave been shown with respect to mitigating wave slam, this functionalitymay be useful in seakeeping in general.

However, this can also be implemented in manned and operator-controlledsystems. For example, embodiments can make slight adjustments inresponse to operator action to reduce wave slam. In some embodiments,the adjustments can be made in anticipation of operator actions,particularly when data has been collected about particular operatorssuch that specific operator tendencies can be compensated for. Some suchembodiments can allow less experienced operators to be able to capablyoperate a vessel in conditions in which the operator may be otherwiseless capable of operating the vessel. In some embodiments, the automatedcontrols can coach the operator, using visual, audible, tactile, orother cues (see acts 23, 24 and 25) during normal operation. In someembodiments, this can be done for training purposes. Note that thisfunctionality can be used to ensure that the vessel takes evasivemaneuvers or actions to minimize or prevent wave slam or other impactsby performing automated controls if the operator is not able to act withsufficient speed and/or sufficient magnitude of action. The automatedcontrols can also compensate for over-reaction by an operator. As noted,when the automated controls compensate for the operator, feedback can beprovided to the operator to indicate that compensation was performedand/or actions that the operator can take in the future to reduceautomated operation control compensation. In some embodiments, anoperator can determine that they are incapable of operating the vesselsafely, and can therefore activate the automated controls to preventand/or reduce the effects of wave slam and other impacts. This allowsfor the implementation of partially manned vessels as operators begin totrust the capabilities of the system.

FIG. 7 illustrates that embodiments may perform act 33 to controldevices. For example, real-time and prediction data may be used as inputfor various devices. For example, embodiments could control a smart seat32 having a hydraulic suspension system to reduce impacts to crew andpassengers. While a smart seat device is indicated, it should beappreciated that other devices can be controlled as well. Indeed, someembodiments may use Internet of Things (IoT) communication methods tocommunicate with various devices to control these devices based onpredicted accelerations, or by using other data available on the boatthat the system will be using to communicate with equipment onboard.

Embodiments may optionally implement various feedback actions. WhileFIG. 7 illustrates implementing system feedback (act 26) andimplementing AI feedback (act 27) the feedback actions are optional,such that either, both, or neither (i.e., open loop control) can beimplemented in various different embodiments of the invention.

With that context, FIG. 7 show that the method can include an act 26 ofimplementing system feedback. System feedback generally adjusts and/orcompensates for inputs to achieve a desired result. In particular,current input values into a system are adjusted (or compensated for)based on differences between current outputs and desired outputs and/orexpired acceleration prediction information. This may include, forexample, comparing real-time acceleration information with desiredacceleration information and/or expired acceleration predictioninformation to determine compensation for inputs. For example, if thereis an acceptable amount of wave slam, and a current accelerationmeasurement indicates that this acceptable amount has been exceeded (inspite of warnings to the operator and/or automatic controls beingimplemented), act 26 can cause information and analysis produced at acts19 and 20 to be modified and/or compensated for, which will result indifferent actions and/or magnitudes of actions being indicated by act 21and being performed by acts 23, 24, 25, 28 and/or 33. For example, if aparticular amount of measured real-time acceleration causes a certainamount of automated steering to be performed by act 28, and thatsteering still results in an unacceptable amount of wave slam, act 26can cause the amount of measured real-time acceleration to be adjustedby adding or subtracting an amount to the real-time measuredacceleration, which will result in a different amount of automatedsteering being performed by act 28 to attempt to reduce the amount ofwave slam. Thus, system feedback can make the output of the system moreaccurate.

Act 26 may be performed independently or with other acts. For instance,the computing unit 2 can compare desired acceleration continuously withreal-time acceleration information to determine the accuracy of theacceleration predictions generated in act 20. Such comparisons typicallyproduce an error result which characterizes the magnitude in the errorof what was desired versus what actually occurred. Optionally, thecomparison results may then be fed back, such as by using a negativefeedback loop, into the real-time data analysis function in the act 18to minimize systematic errors through adjustments in, for example, timeinterval measurements and number of numerical distribution iterations.

In some embodiments, there may be a desire to minimize the differencebetween a current result (i.e., a current amount of wave slam) and anaggregation of all previous expired acceleration prediction information.The feedback principles discussed above can be used to accomplish thisfunctionality.

Act 26 can alternatively or additionally include feeding back comparisonresults into the prediction analysis function performed in the act 20 toimprove prediction accuracy for the remaining duration of a monitoringperiod (e.g., a sea journey) using identified discrepancies. Forexample, the discrepancies identified in act 26 can be assimilated intoact 19 and/or act 20. This can beneficially help determine from whichinformation group (i.e. the expired acceleration prediction informationor the real-time acceleration information for the same period) thediscrepancies originate, which, in turn, can be utilized to reducesystematic errors to the extent possible in both the real-time analysisand/or the prediction analysis for wave slam. In an embodiment, feedbackfrom an operator's use of the prediction information based on enginedata may be analyzed to provide further input into the discrepancy andsystematic error elimination. For example, as discussed previously,information can be collected on particular operators, including theidentity of the operators and tendencies of the operators. This mayinclude, for example, data on throttle control, which shows how theoperator reacted to the presented information from the system, and ingeneral shows the operator's propensity for speed and risk-taking. Thisinformation may be used in acts 19 and/or 20 as appropriate as discussedabove, to minimize wave slam and/or other accelerations of the craft 1.

FIG. 7 also show the method includes act 27 of implementing anartificial intelligence feedback to provide an automated learningfunctionality. This can allow a combination of input data and system andoperator feedback analysis to be used continuously to improve and updatethe real-time acceleration information and prediction information andmechanisms. While the act 26 can improve system output without modifyingthe system components, act 27 can improve the actual system itself byautomatically modifying system components. In particular, AI (typicallyimplemented using machine learning or deep learning) can automaticallyupdate the mechanisms for performing acts 19, 20, 21, 23, 24, 25, 28and/or 33 to create an improved system, rather than simply changing orcompensating for the data input into the system. Act 27 can includeanalyzing data, including expired data predictions, real-time data,desired results, and/or user input regarding the same. For example,embodiments may use various models which can be updated based on expireddata predictions, real-time data, desired results, and/or user input.Updating the models can result in a more accurate system for preventingand/or reducing the effects of wave slam.

For example, various supervised, unsupervised, semi-supervised, and/orreinforcement learning models and systems may be implemented to improvesystem behavior.

Act 27 can include monitoring, and/or recording operator behavior overan extended period of time, improving the accuracy of the acts 19, 20,21, 23, 24, 25, 28 and/or 33 through AI feedback as illustrated above.It will be appreciated that such a personal data log function may beincluded in any of the method acts regardless of whether artificialintelligence is in place or use.

In other embodiments, the data collection process may include the use of360 degree cameras and LIDAR sensing methods or other laser imaging andradar instruments to provide both visual and sensor-based data on wavepatterns (e.g., height, length, and distance to waves). Thisadvantageously can help increase predictive capabilities of the presentdisclosure.

Referring now to FIG. 8, additional details are illustrated. The systemin FIG. 8 uses a server 35. Note that while the server 35 is illustratedas a single entity in FIG. 8. The server 35 may be implemented usingdistributed systems, or other topologies. The server includes a numberof services and other components. Each of the components can beimplemented using appropriate computer hardware and software (which inmany embodiments is shared between the various components), such asprocessors, memory or other storage media for storing computerexecutable instruction that can be executed by the processors to performthe functionality of the components, communication hardware, displaydevices, and other hardware as discussed further herein.

The server 35 includes a data gathering service 37. The data gatheringservice 37 gathers data from sensors, external forecasting services,other data services, other vessels, and/or other data sources asappropriate. The actions of the data gathering services are illustrated,for example, at act 18 described above.

The server 35 further includes a data management service 38. The datamanagement service collects, stores, curates, organizes, and otherwisemanages data collected by the data gathering service 37. Examples ofactions performed by the data management service 38 are described abovein the description of acts 22 and/or 34. Although in some embodiments,the acts performed by act 34 may be performed by a service external tothe server 35.

The server 35 manages various devices and computing units (such asdevice 41, seat 32, computing unit 2, and other devices and computingunits), performs authorization and performs account management throughan infrastructure management service 36. This may include management ofall connected computing units and devices, managing authorization forconnected computing units to communicate data to the serverinfrastructure, and management of individual accounts linked to theconnected computing units. The infrastructure management service mayperform, or at least facilitate the action performed in acts 23, 24, 25,28, and/or 33 illustrated above.

The server 35 further includes a data processing service 39. The dataprocessing service 39 receives data from the data management service 38.The data processing service 39 uses the sourced data (such as timeseries collected data or other collected data), along with existing dataand/or previously generated data to create accurate forecasts andshort-term predictions as described previously. For example, the actionsof acts 19, 20, 21, 26, and/or 27 can be performed by the dataprocessing service 39.

The server infrastructure 35 may also include a user interface 40. Theuser interface 40 can present information to a user (including vesseloperators, vessel owners and/or managers, insurance companies, or otherusers) on real-time processed data, historical data, or other relevantdata. Such data may be presented on online platforms, such as dedicatedwebsites, applications or other web-based or other interfaces. Forexample, some embodiments may implement real-time web dashboardsavailable to users. Thus, some embodiments may implement a new and noveluser interface capable of providing information to users that waspreviously not able to be provided. For example, embodiments can providereal-time alerts in a user interface alerting a user as to predictedwave slams.

Devices (represented by device 41) communicate with the server 35 bymeans of communication hardware and a messaging protocol 45. Forexample, one such protocol may include a publish-subscribe-basedmessaging protocol, including encrypted Message Queuing TelemetryTransport (MQTT), or other comparable modalities. Each connected devicemay be connected to the server 35 in this way. The device 41 may usenetwork communication devices, such as a network connection module 16for network connectivity to enable communication with the serverinfrastructure 35. Note that device 41 represented here is a device thatis in placed on a vessel to collect data and feed to the server, asdescribed above.

In some embodiments, the device 41 may include the computing unit 2illustrated above, and/or other sensor, communication, or other elementsillustrated above. Indeed, in some embodiments, the tools illustratedbelow may be implemented in the computing unit 2, or in other elementsof the device 41 as appropriate.

The device 41 includes one or more tools to perform functions thatenable the analytical processes illustrated herein, including thoseillustrated above in FIG. 7. These tools may be implemented usingvarious hardware and software components, such as various processors,memory or other storage, computer readable instructions stored in thememory or other storage, communication hardware, etc.

One tool that can be included in the device 41 is a data gatherer 42. Insome embodiments, the data gatherer gathers data available in a localenvironment. This could be sensor data (including accelerometers,speedometers, throttle inputs, steering and trim inputs, etc.), datafrom other entities, such as nearby vessels in communication with thecraft 2, or from other sources. This data is communicated to the server35 and captured by the data management service 38.

The device 41 may additionally or alternatively include a data analyzer43 where short-term real-time data collected by the device 41 may bepaired with data maintained on the server infrastructure 35 to evaluatecurrent conditions and make predictions with the support of the server35, data management service 38, and processing service 39. Furthermore,the device 41 may present analyzed real-time or prediction data to theuser of the device 41 through a user interface. Such user interface maybe implemented as a graphical user interface, or other interfaceimplemented at the device 41.

The server 35 and device 41 maintain regular communication in order togather, process, and present analyzed data to the end-user of thesystem.

As discussed above, in other embodiments, collected and/or generatedinformation can be used for fleet management purposes, boating andwatercraft simulations, fleet monitoring, and/or communicating withoperators. In other embodiments, the collected and/or generatedinformation can be used for operator safety. For instance, the computingunit 2 can be operatively coupled to the suspension seat 32 andassociated hydraulic system to adjust suspension in the suspension seat32 for anticipated predicted wave slamming based on collected and/orgenerated information.

In other embodiments, collected and/or generated information can be usedto direct or control speed and/or steering of the craft. For instance,based on collected and/or generated information, a route guidance systemcan direct or instruct on operator to direct the craft to take aspecific path through waves to reduce the likelihood of wave slam.

Accordingly, FIGS. 1-8 provide a number of components, schematics andmechanisms for allowing the generation of real-time accelerationinformation and/or prediction information associated with wave slam. Theinformation can also provide feedback to continuously improve theaccuracy of such information.

Many of the elements described in the disclosed embodiments may beimplemented as modules. A module is defined here as an isolatableelement that performs a defined function and has a defined interface toother elements. The modules described in this disclosure may beimplemented in hardware, a combination of hardware and software,firmware, or a combination, all of which can be behaviorally equivalent.Modules may be implemented using computer hardware in combination withsoftware routine(s) written in a computer language. It may be possibleto implement modules using physical hardware that incorporates discreteor programmable analog and/or digital hardware. Examples of programmablehardware include computers, microcontrollers, microprocessors,application-specific integrated circuits, field programmable gatearrays, and complex programmable logic devices.

As noted above, the software may be embodied on a computer readablemedium which when executed by a processor component of a computer deviceperforms a sequence of acts. The application may be a mobile applicationor application software configured to run on smartphones, tabletscomputers, and/or other mobile devices. Moreover, embodiments of thepresent disclosure may comprise or utilize a special-purpose orgeneral-purpose computer system that includes computer hardware, suchas, for example, one or more processors and system memory, as discussedin greater detail below. Embodiments within the scope of the presentdisclosure also include physical and other computer-readable media forcarrying or storing computer-executable instructions and/or datastructures. Such computer-readable media can be any available media thatcan be accessed by a general-purpose or special-purpose computer system.Computer-readable media that store computer-executable instructionsand/or data structures are computer storage media. Computer-readablemedia that carry computer-executable instructions and/or data structuresare transmission media. Thus, by way of example, and not limitation,embodiments of the disclosure can comprise at least two distinctlydifferent kinds of computer-readable media: computer storage media andtransmission media.

Computer storage media are physical storage media that storecomputer-executable instructions and/or data structures. Physicalstorage media include computer hardware, such as RAM, ROM, EEPROM, solidstate drives (“SSDs”), flash memory, phase-change memory (“PCM”),optical disk storage, magnetic disk storage or other magnetic storagedevices, or any other hardware storage device(s) which can be used tostore program code in the form of computer-executable instructions ordata structures, which can be accessed and executed by a general-purposeor special-purpose computer system to implement the disclosedfunctionality of the disclosure.

Transmission media can include a network and/or data links which can beused to carry program code in the form of computer-executableinstructions or data structures, and which can be accessed by ageneral-purpose or special-purpose computer system. A “network” isdefined as one or more data links that enable the transport ofelectronic data between computer systems and/or modules and/or otherelectronic devices. When information is transferred or provided over anetwork or another communications connection (either hardwired,wireless, or a combination of hardwired or wireless) to a computersystem, the computer system may view the connection as transmissionmedia. Combinations of the above should also be included within thescope of computer-readable media.

Further, upon reaching various computer system components, program codein the form of computer-executable instructions or data structures canbe transferred automatically from transmission media to computer storagemedia (or vice versa). For example, computer-executable instructions ordata structures received over a network or data link can be buffered inRAM within a network interface module (e.g., a “NIC”), and theneventually transferred to computer system RAM and/or to less volatilecomputer storage media at a computer system. Thus, it should beunderstood that computer storage media can be included in computersystem components that also (or even primarily) utilize transmissionmedia.

Computer-executable instructions comprise, for example, instructions anddata which, when executed at one or more processors, cause ageneral-purpose computer system, special-purpose computer system, orspecial-purpose processing device to perform a certain function or groupof functions. Computer-executable instructions may be, for example,binaries, intermediate format instructions such as assembly language, oreven source code.

Those skilled in the art will appreciate that the disclosure may bepracticed in network computing environments with many types of computersystem configurations, including, personal computers, desktop computers,laptop computers, message processors, hand-held devices, multi-processorsystems, microprocessor-based or programmable consumer electronics,network PCs, minicomputers, mainframe computers, mobile telephones,PDAs, tablets, pagers, routers, switches, and the like. The disclosuremay also be practiced in distributed system environments where local andremote computer systems, which are linked (either by hardwired datalinks, wireless data links, or by a combination of hardwired andwireless data links) through a network, both perform tasks. As such, ina distributed system environment, a computer system may include aplurality of constituent computer systems. In a distributed systemenvironment, program modules may be located in both local and remotememory storage devices.

Those skilled in the art will also appreciate that the disclosure may bepracticed in a cloud computing environment. Cloud computing environmentsmay be distributed, although this is not required. When distributed,cloud computing environments may be distributed internationally withinan organization and/or have components possessed across multipleorganizations. In this description and the following claims, “cloudcomputing” is defined as a model for enabling on-demand network accessto a shared pool of configurable computing resources (e.g., networks,servers, storage, applications, and services). The definition of “cloudcomputing” is not limited to any of the other numerous advantages thatcan be obtained from such a model when properly deployed.

A cloud computing model can be composed of various characteristics, suchas on-demand self-service, broad network access, resource pooling, rapidelasticity, measured service, and so forth. A cloud computing model mayalso come in the form of various service models such as, for example,Software as a Service (“SaaS”), Platform as a Service (“PaaS”), andInfrastructure as a Service (“IaaS”). The cloud computing model may alsobe deployed using different deployment models such as private cloud,community cloud, public cloud, hybrid cloud, and so forth.

Some embodiments, such as a cloud computing environment, may comprise asystem that includes one or more hosts that are each capable of runningone or more virtual machines. During operation, virtual machines emulatean operational computing system, supporting an operating system andperhaps one or more other applications as well. In some embodiments,each host includes a hypervisor that emulates virtual resources for thevirtual machines using physical resources that are abstracted from viewof the virtual machines. The hypervisor also provides proper isolationbetween the virtual machines. Thus, from the perspective of any givenvirtual machine, the hypervisor provides the illusion that the virtualmachine is interfacing with a physical resource, even though the virtualmachine only interfaces with the appearance (e.g., a virtual resource)of a physical resource. Examples of physical resources includeprocessing capacity, memory, disk space, network bandwidth, mediadrives, and so forth.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments are contemplated. The various aspects andembodiments disclosed herein are for purposes of illustration and arenot intended to be limiting. Additionally, the words “including,”“having,” and variants thereof (e.g., “includes” and “has”) as usedherein, including the claims, shall be open ended and have the samemeaning as the word “comprising” and variants thereof (e.g., “comprise”and “comprises”).

The invention claimed is:
 1. A method of monitoring accelerations on avessel, comprising the acts of: measuring acceleration on the vesselusing one or more sensors, the one or more sensors communicativelycoupled to a computing unit; generating real-time accelerationinformation representative of an acceleration on the vessel based atleast in part on the measured acceleration from the one or more sensors;obtaining verification of personal information for a specific operatorto allow for obtaining stored data from previous monitoring sessions forthe specific operator; collecting and correlating data for actionsperformed by the specific operator of the vessel; generatingacceleration prediction information representative of a predictedacceleration using the computing unit, the acceleration predictioninformation based at least in part on the generated real-timeacceleration information and the data for actions performed by thespecific operator including obtained stored data from previousmonitoring sessions for the specific operator; using the accelerationprediction information, including using the acceleration predictioninformation generated using the obtained stored data from previousmonitoring sessions for the specific operator, performing user assistedcontrol of trim of the vessel; and presenting information related to theacceleration prediction information to an intended recipient.
 2. Themethod of claim 1, wherein presenting the information related to theacceleration prediction information to the intended recipient includesdisplaying the information to the intended recipient.
 3. The method ofclaim 1, wherein presenting the information related to the accelerationprediction information to an intended recipient includes providing analarm to the intended recipient.
 4. The method of claim 1, wherein thesensors and the computing unit are located on the vessel.
 5. The methodof claim 1, wherein the computing unit is located remote to the vesselcarrying the one or more sensors.
 6. The method of claim 1, furthercomprising controlling suspension in a suspension seat based at least inpart on information from the one or more sensors.
 7. The method of claim1, further comprising, as part of an automated control system,performing fully automatic controlling of trim, steering and/or speed ofthe vessel based at least in part on information from the one or moresensors.
 8. The method of claim 1, further comprising performing userassisted control of steering and/or speed of the vessel based at leastin part on information from the one or more sensors by at least one ofamplifying or dampening user actions.
 9. The method of claim 1, whereinpresenting the information related to the acceleration predictioninformation to an intended recipient includes presenting suchinformation via a web-based interface.
 10. The method of claim 1,wherein presenting the information related to the accelerationprediction information to an intended recipient includes presenting suchinformation via a simulation system.
 11. The method of claim 1, whereinpresenting the information related to the acceleration predictioninformation to an intended recipient includes presenting suchinformation via at least one of an augmented reality device or mobilecomputing devices.
 12. The method of claim 1, wherein the one or moresensors include at least one of a 360 degree camera, laser instruments,or radar instruments.
 13. The method of claim 1, wherein presenting theinformation related to the acceleration prediction information to anintended recipient includes presenting information based on informationobtained via a 360 degree camera, laser instruments, and/or radarinstruments.
 14. The method of claim 1, wherein generating the at leastone of the generated real-time acceleration information and theacceleration prediction information includes LIDAR sensing methods. 15.The method of claim 1 further comprising, performing system feedback tocompensate for inputs into the computing unit.
 16. The method of claim 1further comprising, performing artificial intelligence or machinelearning feedback to improve systems implemented by the computing unitby automatically modifying system output.
 17. The method of claim 1,further comprising compiling accelerations experienced by specific crewmembers.
 18. The method of claim 1, further comprising: obtaininginformation about conditions experienced by a different vessel proximatethe vessel; and wherein generating acceleration prediction informationrepresentative of a predicted acceleration using the computing unit isbased at least in part on the information about conditions experiencedby the different vessel proximate the vessel.
 19. A monitoring systemfor a vessel comprising: one or more sensors configured to measureacceleration on the vessel; a computing unit communicatively coupled tothe one or more sensors, wherein the computing unit is configured togenerate real-time acceleration information representative of anacceleration on the vessel based at least in part on the measuredacceleration from the one or more sensors; wherein the computing unit isconfigured to obtain verification of personal information for a specificoperator to allow for obtaining stored data from previous monitoringsessions for the specific operator; wherein the computing unit isconfigured to collect, process, and correlate data for actions performedby the specific operator of the vessel; further wherein the computingunit is configured to generate acceleration prediction informationrepresentative of a predicted acceleration using the computing unit, theacceleration prediction information based at least in part on thegenerated real-time acceleration information and the data for actionsperformed by the specific operator including obtained stored data fromprevious monitoring sessions for the specific operator; wherein thecomputing unit is configured to, using the acceleration predictioninformation, including using the acceleration prediction informationgenerated using the obtained stored data from previous monitoringsessions for the specific operator, cause user assisted control of trimof the vessel to be performed; and a user interface coupled to thecomputing unit, wherein the user interface is configured to presentinformation related to the acceleration prediction information to anintended recipient.
 20. A computing system comprising: one or moreprocessors; one or more computer readable media coupled to the one ormore processors, the one or more computer readable media comprisingcomputer executable instructions that when executed by the one or moreprocessors configure the computing system to implement an accelerationmonitor system, including causing the one or more processors to performthe following: obtaining measurements of acceleration on a vessel viaone or more sensors; generating real-time acceleration informationrepresentative of an acceleration on the vessel based at least in parton the obtained acceleration force measurements from the one or moresensors; obtaining verification of personal information for a specificoperator to allow for obtaining stored data from previous monitoringsessions for the specific operator; collecting and correlating data foractions performed by the specific operator of the vessel; generatingacceleration prediction information representative of a predictedacceleration, the acceleration prediction information based at least inpart on the generated real-time acceleration information and the datafor actions performed by the specific operator including obtained storeddata from previous monitoring sessions for the specific operator; usingthe acceleration prediction information, including using theacceleration prediction information generated using the obtained storeddata from previous monitoring sessions for the specific operator,causing user assisted control of trim of the vessel to be performed; andpresenting information related to the acceleration predictioninformation to an intended recipient.